Fil

Just talking about the significance for AI (...) the other big thing you’ve heard me talk about is the difference between this and Deep Blue. So Deep Blue is a hand-crafted program where the programmers distilled the information from chess grandmasters into specific rules and heuristics, whereas we’ve imbued AlphaGo with the ability to learn and then it’s learnt it through practice and study, which is much more human-like.

sur la capacité de l’approche :

We think this algorithm can work without any supervision. The Atari games that we did last year, playing from the pixels — that didn’t bootstrap from any human knowledge, that started literally from doing random things on screen.

Q: The main future uses of AI that you’ve brought up this week have been healthcare, smartphone assistants, and robotics. (...)A: the sort of things you’ll see this kind of AI do is medical diagnosis of images and then maybe longitudinal tracking of vital signs or quantified self over time, and helping people have healthier lifestyles. (…) we’re just doing it all for free

sur la capacité de calcul :

AlphaGo doesn’t actually use that much hardware in play, but we needed a lot of hardware to train it and do all the different versions and have them play each other in tournaments on the cloud. That takes quite a lot of hardware to do efficiently, so we couldn’t have done it in this time frame without those [Google] resources.

What I’m really excited to use this kind of AI for is science, and advancing that faster. I’d like to see AI-assisted science where you have effectively AI research assistants that do a lot of the drudgery work and surface interesting articles, find structure in vast amounts of data, and then surface that to the human experts and scientists who can make quicker breakthroughs.